Hidden Markov Measure Field Models for Image Segmentation

@article{Marroqun2003HiddenMM,
  title={Hidden Markov Measure Field Models for Image Segmentation},
  author={Jos{\'e} L. Marroqu{\'i}n and Edgar Arce Santana and Salvador Botello Rionda},
  journal={IEEE Trans. Pattern Anal. Mach. Intell.},
  year={2003},
  volume={25},
  pages={1380-1387}
}
Parametric image segmentation consists of finding a label field that defines a partition of an image into a set of nonoverlapping regions and the parameters of the models that describe the variation of some property within each region. A new Bayesian formulation for the solution of this problem is presented, based on the key idea of using a doubly stochastic prior model for the label field, which allows one to find exact optimal estimators for both this field and the model parameters by the… CONTINUE READING
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References

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Hidden Markov Measure Field Models for Image Segmentation

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